How did we Machine learning: Analysis and prediction phase The first decade of the 2000s marked the rapid advance viewed machine learning as an incredibly powerful field of various machine learning techniques that could analyze of AI for analyzing data, finding patterns, generating get here? massive amounts of online data to draw conclusions – insights, making predictions and automating tasks at a or “learn” – from the results. Since then, companies have pace and on a scale that was previously impossible. Milestones in the journey Deep learning: Vision and speech phase to generative AI The 2010s produced advances in AI’s that search engines and self-driving cars use perception capabilities in the field of machine to classify and detect objects, as well as the learning called deep learning. Breakthroughs voice recognition that allows popular AI speech in deep learning enable the computer vision assistants to respond to users in a natural way. Generative AI: Enter the language-mastery phase Building on exponential increases in the size and phase in the abilities of language-based AI applications. Models capabilities of deep learning models, the 2020s will be such as this will have far-reaching consequences for business, about language mastery. The GPT-4 language model, since language permeates everything an organization does day to developed by OpenAI, marks the beginning of a new 2 day—its institutional knowledge, communication and processes. A new era of generative AI for everyone | 4